NEDD4L suppresses PD-L1 expression and enhances anti-tumor immune response in A549 cells

Zhong Bin,Zheng Jie,Wen Huilan,Liao Xinhui,Chen Xingxiang,Rao Yunwei,Yuan Ping 한국유전학회 2022 Genes & Genomics Vol.44 No.9

Background: Non-small cell lung cancer (NSCLC) poses a salient threat to public health. E3 ubiquitin ligase commonly functions as an anti-tumor role. Objective: This study probed the effect of E3 ligase NEDD4L on A549 cells. Methods: NEDD4L expression in NSCLC and its correlation with NSCLC patient's prognosis were predicted and verified. PD-L1 protein level was measured, and the correlation between NEDD4L and PD-L1 was analyzed. The effects of NEDD4L overexpression on the binding of NEDD4L to PD-L1 and ubiquitination level of PD-L1 were examined. Xenograft tumor model was established in mice. The volume and weight of xenograft tumors were recorded. The proportion of CD8+ T cells and contents of IL-2 and INF-γ were detected. Results: NEDD4L expression was downregulated in NSCLC tissues and A549 cells, and correlated with poor prognosis of NSCLC patients. PD-L1 was upregulated in NSCLC and negatively correlated with NEDD4L. Overexpression of NEDD4L upregulated ubiquitination level of PD-L1 and reduced protein level of PD-L1. Overexpression of NEDD4L decreased tumor volume and weight and enhanced proportion of CD8+ T cells and contents of IL-2 and INF-γ. Conclusions: Collectively, overexpression of NEDD4L suppressed PD-L1 protein level through ubiquitination, thereby enhancing anti-tumor immune response and retarding NSCLC progression.

A Self-Powered RFID Sensor Tag for Long-Term Temperature Monitoring in Substation

Zhongbin Chen,Fangming Deng,Yigang He,Zhen Liang,Zhihui Fu,Chaolong Zhang 대한전기학회 2018 Journal of Electrical Engineering & Technology Vol.13 No.1

Radio frequency identification (RFID) sensor tag provides several advantages including battery-less operation and low cost, which are suitable for long-term monitoring. This paper presents a self-powered RFID temperature sensor tag for online temperature monitoring in substation. The proposed sensor tag is used to measure and process the temperature of high voltage equipments in substation, and then wireless deliver the data. The proposed temperature sensor employs a novel phased-locked loop (PLL)-based architecture and can convert the temperature sensor in frequency domain without a reference clock, which can significantly improve the temperature accuracy. A twostage rectifier adopts a series of auxiliary floating rectifier to boost its gate voltage for higher power conversion efficiency. The sensor tag chip was fabricated in TSMC 0.18㎛ 1P6M CMOS process. The measurement results show that the proposed temperature sensor tag achieve a resolution of 0.15 ℃ /LSB and a temperature error of -0.6/0.7 ℃ within the range from -30 ℃ to 70 ℃. The proposed sensor tag achieves maximum communication distance of 11.8 m.

A Self-Powered RFID Sensor Tag for Long-Term Temperature Monitoring in Substation

Chen, Zhongbin,Deng, Fangming,He, Yigang,Liang, Zhen,Fu, Zhihui,Zhang, Chaolong The Korean Institute of Electrical Engineers 2018 Journal of Electrical Engineering & Technology Vol.13 No.1

Radio frequency identification (RFID) sensor tag provides several advantages including battery-less operation and low cost, which are suitable for long-term monitoring. This paper presents a self-powered RFID temperature sensor tag for online temperature monitoring in substation. The proposed sensor tag is used to measure and process the temperature of high voltage equipments in substation, and then wireless deliver the data. The proposed temperature sensor employs a novel phased-locked loop (PLL)-based architecture and can convert the temperature sensor in frequency domain without a reference clock, which can significantly improve the temperature accuracy. A two-stage rectifier adopts a series of auxiliary floating rectifier to boost its gate voltage for higher power conversion efficiency. The sensor tag chip was fabricated in TSMC $0.18{\mu}m$ 1P6M CMOS process. The measurement results show that the proposed temperature sensor tag achieve a resolution of $0.15^{\circ}C$/LSB and a temperature error of $-0.6/0.7^{\circ}C$ within the range from $-30^{\circ}C$ to $70^{\circ}C$. The proposed sensor tag achieves maximum communication distance of 11.8 m.

Characteristics of Cracks in two Paddy Soils and their Impacts on Preferential Flow

Xinhua Peng,Zhongbin Zhang 한국토양비료학회 2014 한국토양비료학회 학술발표회 초록집 Vol.2014 No.6

UAV Remote Sensing Image Mosaic and Its Application in Agriculture

Yinjiang Jia,Zhongbin Su,Weizheng Shen,Jianqing Yuan,Zhenan Xu 보안공학연구지원센터 2016 International Journal of Smart Home Vol.10 No.5

UAV remote sensing image has the characteristics of higher spatial resolution, fine timeliness and high flexibility. It is widely used in many fields such as agriculture, forestry, soil resources and so on. Especially in agriculture, it plays an important role in information acquisition of agricultural production and agricultural condition monitoring. In the experiment, high-definition digital camera and multi-spectral camera are used to capture the visible light and near-infrared remote sensing image. Two pieces of 3m*3m calibration cloth is used for radiometric calibration and SIFT algorithm was used for image mosaic. This paper discusses the application of remote sensing image in agriculture, including rice lodging monitoring, diseases and pests monitoring, crop growth monitoring and crop nutrient diagnosis. The results show that UAV remote sensing provides an effective means for agricultural condition information acquisition, and has wide application prospect.

Intercomparison of ADC-Lite Images on UAV and TM Simulation Data for Soybean Leaf Area Index Retrieval

Qi Zhang,Zhongbin Su,Guijun Yang,Minghui Wang,Weizheng Shen,Xiaowei Teng,Jinhui Dong 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.7

Currently, TM images has a very high practical value and widely used in all aspects of agricultural. Unmanned Aerial Vehicles (UAV) remote sensing platform mounted ADC-Lite multi-spectral sensor has consistent channels response functions with TM sensor in TM2, TM3 and TM4, demonstrated to compete with TM sensor, due to low operational cost, high operational flexibility, high spatial resolution of imagery (0.018m with flight altitude 50m) and heterogeneity both at time and spatial-scale. In order to make sure whether it has widely used as TM sensor, moreover, the aim of this work is to assess ADC-Lite performance such as its adaptability and practicability. In this paper, ADC-Lite multi-spectral data, ground truth ASD hyperspectral and Leaf area index (LAI) data were acquired in soybean planting area, Jiaxiang County, Shandong Province on September18th, 2015. Since the ADC-Lite has different spatial scales with TM, this paper used TM simulation data transformed by ground truth ASD data, constructed LAI inversion model by empirical model based on two sensors and ground measured data, using 5 vegetation indices: ratio vegetation index (RVI), normalized difference vegetation index (NDVI), soil adjust vegetation index (SAVI), difference vegetation index (DVI) and triangular vegetation index (TVI). Determination coefficient R2, root mean square error (RMSE) and the estimation accuracy (EA) 3 indicators were acquired to assess the model. This work suggests that the established model of ADC-Lite sensor with TM simulation sensor has high consistency in accuracy. NDVI linear regression model derived from both of them presented a strong correlation with ground-measured LAI. It’s preliminarily shown that ADC-Lite images assess soybean LAI is feasible. This is anticipated to have tremendous implications that ADC-Lite can be made supplement for existing satellites, aerial and ground sensing, provide important information for Crop condition monitoring and critical data to support crop maturity, nutrition monitoring and fertilization management.

Research on UAV Remote Sensing Image Mosaic Method Based on SIFT

Yinjiang Jia,Zhongbin Su,Qi Zhang,Yu Zhang,Yunhao Gu,Zhongqiu Chen 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.11

UAV remote sensing, as a new method of remote sensing, has the characteristics of higher spatial resolution, fine timeliness and high flexibility. It is widely used in the field of natural disaster monitoring, urban planning, resource investigation, and has become one of the indispensable method of remote sensing data acquisition. However, because the UAV remote sensing platform is limited by the flight height and focal length of camera, the acquired image size is smaller, single image can’t cover the entire target area. Therefore, image mosaic has become a key technology to solve the problem. Image matching and image fusion are the key techniques of image mosaic. Due to the good robustness of image scaling, translation and rotation, this paper uses the SIFT algorithm to realize image matching of UAV. Since the feature extraction may produce false matches, RANSAC algorithm is applied to the feature point purification points. According to the seam-line in jointing overlap region, weighted fusion algorithm is applied to realize the image seamless splicing.

A Distributed Clustering Algorithm with Optimal Search Model for Wireless Sensor Networks

Tao Lü,ZhongBin CAI,YuYu ZHU 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.9

In view of the operating mode of wireless sensor networks, the node initial probability and channel listening, a distributed clustering algorithm DCOS based on the optimal search model is proposed, along with the corresponding mathematical optimization model. The goal of model optimization is to find a feasible allocation scheme for search resource so that the probability of successful communication reaches its maximum under the constrained condition for search resource. Clustering algorithm is designed to balance the network energy consumption, thereby maximizing network lifetime. In the clustering algorithm, the cluster head is generated in the comprehensive consideration of the minimum number of nodes in the overlay network, and the node residual energy and the number of neighboring nodes, during the operation of the network, setting the maximum wait time for cluster heads may avoid the their energy consumption. Analysis and simulation results show that, compared to several important clustering algorithms, the performance of DCOS is proven to be superior in balancing node energy consumption and prolonging the network lifetime.

Near-infrared Detection of Straw Cellulose by Orthogonal Signal Correction and Partial Least Squares

Qingming Kong,Zhongbin Su,Weizheng Shen,Mingming Han,Bohan Li,Xudong Wang 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.5

Orthogonal signal correction (OSC)and partial least squares(PLS)were used during the pretreatment of straw to reduce environmental noise and prediction models were established for near-infrared detection of straw cellulose. Tests were run with soybean stalk as the object of study. Test results indicated that compared to a model established using a traditional denoising method, the determination coefficients for calibration set models established by second derivative+smoothing and OSC were 0.9318595 and 0.9328905 respectively while the root mean square error for calibration (RMSEC) were 0.6762902 and 0.6696454. For an OSC-PLS regression model with a factor of 8, the relative standard deviation of a prediction model was less than 5%. In the OSC denoising process, the root mean square error fluctuated with the increasing number of PLS factors. Compared to the second derivative-smoothing denoising, OSC-PLS denoising removed the non-correlated variation from spectra and improved interpretation ability of variation while the analysis and convergence were expedited. It was therefore concluded that OSC-PLS denoising could be used to realize the rapid and accurate near-infrared detection of straw cellulose.

Remote Monitoring of Heading Rice Growing and Nitrogen Content Based on UAV Images

Yu Zhang,Zhongbin Su,Weizheng Shen,Renshan Jia,Jiling Luan 보안공학연구지원센터 2016 International Journal of Smart Home Vol.10 No.7

Rice heading is the critical stage of the growth of rice, rice plants are relatively large, field canopy, poor resistance, and coincided with the high temperature and rainy weather, pests and diseases are more prone period. Therefore, the use of UAV to monitor the growth status of rice, easy to understand rice growth and nutritional status, in order to achieve high-quality, high yield, efficient purpose. This article is the field experiments under different nitrogen levels, using UAV monitoring multispectral images of rice, by reference remote sensing spectral indices, derived green normalized difference vegetation index (GNDVI) relative to other spectral index is more suitable for rice field biomass inversion modeling. At the same time, this study is based on the inversion model, implemented the rice growing and nitrogen content graded by ISODATA methods in ENVI. Achieved classification on rice growth and nitrogen remote sensing thematic map in ArcGIS, to provide timely and accurate information for rice seedling diagnosis and management decision, has reached the purpose of rice production precise management.